Abstract

Conserving biodiversity and combating ecological hazards require cost-effective allocation of limited resources among potential management projects. Project priorities, however, can change over time as underlying social-ecological systems progress, novel priorities emerge, and management capabilities evolve. Thus, reallocation of ongoing investments in response to shifting priorities could improve management outcomes and address urgent demands, especially when additional funding is not available immediately. Resource reallocation, however, could incur transaction costs, require additional monitoring and reassessment, and be constrained by ongoing project commitments. Such complexities may prevent managers from considering potentially beneficial reallocation strategies, reducing long-term effectiveness. We propose an iterative project prioritization approach, based on marginal return-on-investment estimation and portfolio optimization, that guides resource reallocation among ongoing and new projects. Using simulation experiments in 2 case studies, we explored how this approach can improve efficacy under varying reallocation constraints, frequencies, costs, and rates of project portfolio change. Periodic budget reallocation could enhance the management of stochastically emerging invasive weeds in Australia and thus reduce the overall risk by up to 50% compared with a static budget. Reallocation frequency and the rate of new weed incursion synergistically increased the conservation gains achieved by allowing unconstrained reallocation. Conversely, budget reallocation would not improve the International Union for Conservation of Nature conservation status of threatened Australian birds due to slow rates of transition among conservation states; extinction risk could increase if portfolio reassessment is costly. Although other project prioritization studies may recommend periodic reassessment and reallocation, our findings revealed conditions when reallocation is valuable and demonstrated a structured approach that can help conservation agencies schedule and implement iterative budget-allocation decisions cost-effectively.

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